Tim@open_founder
SERV Reasoning is entirely model-agnostic
Frontier models. Open-source models. Local infra. Enterprise stacks. Government systems. It can layer on top of any model and improve performance + reduce overhead with a single line of code.
It was purposely designed like this from the start, because institutions don’t all want the same AI stack.
Some are comfortable using GPT-class or Claude-style frontier models. Others need open-source models running on their own infrastructure for data control, compliance, or sovereignty.
SERV Reasoning works across all of it, which massively expands the surface area we can serve.
The total addressable market is.... simply huge.
And because adoption only requires a one-line code change, the switching cost is near-zero. No painful migration. No rebuilding legacy systems. No months of integration work.
That unlocks three things at once:
Better reasoning, so AI systems actually work in production.
Lower inference costs, allowing teams to scale agents 5x, 10x, 20x, even 50x cheaper.
Minimal adoption friction, making enterprise and government rollout dramatically easier.
Institutional agentic AI growth is being unlocked by SERV Reasoning.
The beta is not even the tip of the iceberg.
